Experis Cross Border connects some of the largest and most innovative companies to the highest skilled workers globally, regardless of location
Our client is the world's leading provider of enterprise open-source software solutions, utilizing a community-driven approach to deliver high-performing Linux, cloud, container, and Kubernetes technologies. With a presence in over 40 countries, our associates have the flexibility to choose a work environment that best suits their needs, ranging from in-office to fully remote options.
The Role:
In this role, you will serve as a technical expert in the areas of explainable AI and fairness, focusing on the responsible AI features of the open-source Open Data Hub project. Your primary responsibilities will involve active participation in key open-source communities, including KServe, TrustyAI, Kubeflow, and others.
You will work as an integral member of a dynamic development team, contributing to the rapid design, security, development, testing, and deployment of model-serving capabilities, trustworthy AI solutions, and model registry functionalities.
Job Responsibilities:
- Serve as a thought leader and influencer in the MLOps, LLM Guardrails, Explainable AI, Fairness, and Bias domains, contributing to the development of a vibrant open-source ecosystem for Open Data Hub and OpenShift AI.
- Contribute to the design and integration of model fairness and bias metrics, as well as explainable AI algorithms, within the OpenShift AI product suite.
- Act as a Subject Matter Expert (SME) in Explainable AI, providing expertise in customer-facing discussions, delivering presentations at technical conferences, and advocating for OpenShift AI within internal communities of practice.
- Conduct research and design innovative features for open-source MLOps communities, including KServe and TrustyAI, to enhance their capabilities and impact.
- Collaborate closely with product management and customer engineering teams to identify opportunities for expanding and refining product functionalities.
- Mentor, guide, and influence a distributed team of engineers, fostering collaboration and promoting professional development within the team.
Requirements:
- Extensive experience in research and development within the field of Explainable Artificial Intelligence (XAI), with a particular focus on Guardrails for Large Language Models (LLMs), model-agnostic interpretability methods, bias detection and mitigation, as well as metrics for evaluating fairness, transparency, and interpretability in complex AI models.
- Recent, hands-on experience in deploying and maintaining machine learning models in production environments, specifically related to Explainable AI.
- Demonstrated technical leadership capabilities, with a proven track record of guiding and influencing teams and projects.
- A strong commitment to writing and maintaining reliable, high-quality code.
- Practical experience with Kubernetes, including hands-on deployment and management of containerized applications.
- Comfortable working effectively within a distributed, remote team environment.
- Exceptional written and verbal communication skills, with proficiency in the English language.
Qualification:
- A Bachelor's degree in Statistics, Mathematics, Computer Science, or a related quantitative field, or equivalent professional expertise. A Master's or PhD in Machine Learning or Natural Language Processing (NLP) is highly desirable.
- Demonstrated experience in engineering, consulting, or a related domain involving model serving and monitoring, model registry, explainable AI, deep neural networks, preferably within a customer-facing environment or supporting a data science team.
- Extensive hands-on experience with Kubernetes and/or OpenShift.
- Advanced proficiency and experience with programming languages such as Python, Java, or Go.
- Familiarity with widely used Python machine learning libraries, including but not limited to PyTorch, TensorFlow, Scikit-Learn, and Hugging Face.
This is a permanent opportunity and requires the legal right to work in the UK or Europe. Remote work is possible but candidates willing to Ireland are preferred
